Autonomously acting robot whose activity amount is controlled

ABSTRACT

A robot includes an operation control unit that selects a motion of the robot, a drive mechanism that executes a motion selected by the operation control unit, and a remaining battery charge monitoring unit that monitors a remaining charge of a rechargeable battery. Behavioral characteristics of the robot change in accordance with the remaining battery charge. For example, a motion with a small processing load is selected at a probability that is higher the smaller the remaining battery charge. Referring to consumption plan data that define a power consumption pace of the rechargeable battery, the behavioral characteristics of the robot may be caused to change in accordance with a difference between the remaining battery charge scheduled in the consumption plan data and the actual remaining battery charge.

RELATED APPLICATIONS

The present application is a continuation of International ApplicationNo. PCT/JP2017/025082, filed Jul. 10, 2017, which claims priority fromJapanese Application No. 2016-137188, filed Jul. 11, 2016, thedisclosures of which applications are hereby incorporated by referenceherein in their entirety.

Technical Field

The present invention relates to a robot that autonomously selects anaction in accordance with an internal state or an external environment.

Background Art

A human keeps a pet in a search for solace. Meanwhile, for variousreasons such as not being able to secure sufficient time to look after apet, not having a living environment in which a pet can be kept, havingan allergy, or hating the thought of being parted by death, there aremany people who give up on keeping a pet. If there were a robot thatperformed the role of a pet, it may be that people who cannot keep a petwould also be provided with the kind of solace that a pet provides(refer to Patent Document 1). Although robot technology has advancedswiftly in recent years, the technology has not advanced so far as torealize a presence as a pet-like companion.

CITATION LIST Patent Literature

-   Patent Document 1: JP-A-2000-323219

Non-Patent Literature

-   Non-patent Document 1: Kazuo YANO, “Invisible Hand of Data”,    Soshisha, July, 2014

SUMMARY OF INVENTION Technical Problem

A living creature recovers vitality by eating and sleeping. Vitality ofa living creature decreases when the living creature is hungry orlacking in sleep. A robot recovers vitality, that is, energy foractivity, by being charged. Charging for a robot is similar to eatingand sleeping for a living creature. The inventor thinks that byconsidering a relationship between a remaining battery charge and anactivity amount, human-like or animal-like behavioral characteristicscan also be realized by a robot. It is thought that if there were arobot that can autonomously select a human-like or animal-like action,empathy toward the robot could be greatly increased.

The invention, having been completed based on the heretofore describedidea, has a main object of providing technology for rationallycontrolling an activity amount of a robot.

Solution to Problem

An autonomously acting robot in an aspect of the invention includes anoperation control unit that selects a motion of the robot, a drivemechanism that executes a motion selected by the operation control unit,and a remaining battery charge monitoring unit that monitors a remainingcharge of a rechargeable battery.

The operation control unit causes behavioral characteristics of therobot to change in accordance with the remaining battery charge.

An autonomously acting robot in another aspect of the invention includesan operation control unit that selects a motion of the robot, a drivemechanism that executes a motion selected by the operation control unit,a remaining battery charge monitoring unit that monitors a remainingcharge of a rechargeable battery, and a recognizing unit that determinesan occurrence of an event.

When a predetermined priority event occurs during charging, theoperation control unit selects a motion responding to the priorityevent, even though charging is not completed.

An autonomously acting robot in another aspect of the invention includesan operation control unit that selects a motion of the robot, and adrive mechanism that executes a motion selected by the operation controlunit.

The operation control unit selects a motion of the robot at a selectionprobability such that a negative correlation with respect to aprocessing load of the motion is established.

An autonomously acting robot in another aspect of the invention includesan operation control unit that selects a motion of the robot, a drivemechanism that executes a motion selected by the operation control unit,and a mode selection unit that selects either a normal mode or a powersaving mode wherein a power supply is restricted more than in the normalmode.

When a predetermined return event occurs when set to the power savingmode, the operation selection unit executes a start-up motion correlatedto the return event, and the mode selection unit changes from the powersaving mode to the normal mode.

An autonomously acting robot in another aspect of the invention includesan operation control unit that selects a motion of the robot, a drivemechanism that executes a motion selected by the operation control unit,and a mode selection unit that selects either a normal mode or a powersaving mode wherein a power supply is restricted more than in the normalmode.

When set to the power saving mode, the mode selection unit changes fromthe power saving mode to the normal mode with a moving object beingdetected as a condition.

An autonomously acting robot in another aspect of the invention includesan actuator, an operation control unit that transmits an actuatingsignal to the actuator, and a remaining battery charge monitoring unitthat monitors a remaining charge of a rechargeable battery.

The operation control unit limits power supplied to the actuator morethan at a normal time when the remaining battery charge reaches apredetermined threshold or lower.

An autonomously acting robot in another aspect of the invention includesan operation control unit that selects a motion of the robot, a drivemechanism that executes a motion selected by the operation control unit,a mode selection unit that selects either a first mode or a second mode,and an eye generating unit that causes a pupil image to change inaccordance with the first mode and the second mode.

The mode selection unit changes to the second mode when a predeterminedtransition condition is satisfied in the first mode, and the eyegenerating unit causes the pupil image to move to the left and right inthe first mode, and causes the pupil image to close in the second mode.

An autonomously acting robot in another aspect of the invention includesan operation control unit that selects a motion of the robot, a drivemechanism that executes a motion selected by the operation control unit,a remaining battery charge monitoring unit that monitors a remainingcharge of a rechargeable battery, and a mode selection unit that selectseither a normal mode or a power saving mode wherein a power supply isrestricted more than in the normal mode.

The operation control unit selects an external charger as a movementtarget point when the remaining charge of the rechargeable batteryreaches a predetermined threshold or less, and the mode selection unitchanges from the normal mode to the power saving mode when an obstacleexists on a path of movement to the charger.

Advantageous Effects of Invention

According to the invention, empathy toward a robot is easily increased.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1A is a front external view of a robot.

FIG. 1B is a side external view of the robot.

FIG. 2 is a sectional view schematically representing a structure of therobot.

FIG. 3 is a configuration diagram of a robot system.

FIG. 4 is a schematic view of an emotion map.

FIG. 5 is a hardware configuration diagram of the robot.

FIG. 6 is a functional block diagram of the robot system.

FIG. 7 is a data structure diagram of a load table.

FIG. 8 is a data structure diagram of a motion selection table.

FIG. 9 is a schematic diagram showing a relationship between consumptionplan data and motion selection.

FIG. 10 is a schematic diagram of a consumption plan selection table.

FIG. 11 is a schematic diagram showing a relationship between processingload and selection probability.

FIG. 12 is a flowchart showing a process when a priority event occursduring charging.

FIG. 13 is a functional block diagram of the robot system in a firstmodified example.

FIG. 14 is an external view of an eye image.

FIG. 15 is an operating mode transition diagram.

FIG. 16 is an external view of a charging station.

FIG. 1A is a front external view of a robot 100. FIG. 1B is a sideexternal view of the robot 100.

The robot 100 in this embodiment is an autonomously acting robot thatdetermines an action or gesture based on an external environment and aninternal state. The external environment is recognized using variouskinds of sensor, such as a camera or a thermosensor. The internal stateis quantified as various parameters that express emotions of the robot100. These will be described hereafter.

With indoor action as a precondition, the robot 100 has, for example, aninterior of an owner's home as an action range. Hereafter, a humaninvolved with the robot 100 will be called a “user”, and a user forminga member of a home to which the robot 100 belongs will be called an“owner”.

A body 104 of the robot 100 has a rounded form all over, and includes anouter skin formed of a soft material having elasticity, such asurethane, rubber, a resin, or a fiber. The robot 100 may be clothed. Bythe body 104, which is rounded, soft, and pleasant to touch, beingadopted, the robot 100 provides a user with a sense of security and apleasant tactile sensation.

A total weight of the robot 100 is 15 kilograms or less, preferably 10kilograms or less, and more preferably still 5 kilograms or less. Amajority of babies start to walk by themselves by 13 months after birth.An average weight of a baby 13 months after birth is a little over 9kilograms for boys, and a little under 9 kilograms for girls. Because ofthis, when the total weight of the robot 100 is 10 kilograms or less, auser can hold the robot 100 with an effort practically equivalent tothat of holding a baby that cannot walk by itself. An average weight ofa baby less than 2 months after birth is less than 5 kilograms for bothboys and girls. Consequently, when the total weight of the robot 100 is5 kilograms or less, a user can hold the robot 100 with an effortpractically equivalent to that of holding a very young baby.

Advantages of a user holding the robot 100 easily, and wanting to holdthe robot 100, are realized by the attributes of appropriate weight androundness, softness, and pleasantness of touch. For the same reasons, aheight of the robot 100 is desirably 1.2 meters or less, or preferably0.7 meters or less. Being able to be held is an important concept of therobot 100 in this embodiment.

The robot 100 includes three wheels for three-wheeled traveling. Asshown in the drawings, the robot 100 includes a pair of front wheels 102(a left wheel 102 a and a right wheel 102 b) and one rear wheel 103. Thefront wheels 102 are drive wheels, and the rear wheel 103 is a drivenwheel. Although the front wheels 102 have no steering mechanism,rotational speed and a direction of rotation can be individuallycontrolled. The rear wheel 103 is formed of a so-called omni wheel, androtates freely in order to cause the robot 100 to move forward and back,and left and right. By controlling so that the rotational speed of theright wheel 102 b is greater than that of the left wheel 102 a, therobot 100 can turn left or rotate counterclockwise. By controlling sothat the rotational speed of the left wheel 102 a is greater than thatof the right wheel 102 b, the robot 100 can turn right or rotateclockwise.

The front wheels 102 and the rear wheel 103 can be completely stored inthe body 104 using a drive mechanism (a pivoting mechanism and a linkingmechanism). A greater portion of each wheel is hidden by the body 104when traveling too, but when each wheel is completely stored in the body104, the robot 100 is in a state of being unable to move. That is, thebody 104 descends, and sits on a floor surface F, in accompaniment to anoperation of the wheels being housed. In the sitting state, a flatseating face 108 (a ground bottom face) formed in a bottom portion ofthe body 104 comes into contact with the floor surface F.

The robot 100 has two arms 106. The arms 106 do not have a function ofgripping an object. The arms 106 can perform simple actions such asraising, waving, and oscillating. The two arms 106 can also becontrolled individually.

A camera is incorporated in an eye 110. The eye 110 is also capable ofan image display using a liquid crystal element or an organic ELelement. In addition to the camera incorporated in the eye 110, varioussensors, such as a highly directional microphone and an ultrasonicsensor, are mounted in the robot 100. Also, a speaker is incorporated,and the robot 100 is also capable of simple speech.

A horn 112 is attached to a head portion of the robot 100. As the robot100 is lightweight, as heretofore described, a user can also lift up therobot 100 by grasping the horn 112.

FIG. 2 is a sectional view schematically representing a structure of therobot 100.

As shown in FIG. 2 , the body 104 of the robot 100 includes a base frame308, a main body frame 310, a pair of wheel covers 312 made of resin,and an outer skin 314. The base frame 308 is formed of metal, andsupports an internal mechanism together with configuring a shaft of thebody 104. The base frame 308 is configured by an upper plate 332 and alower plate 334 being linked vertically by a multiple of side plates336. A sufficient interval is provided between the multiple of sideplates 336 so that ventilation is possible. A battery 118, a controldevice 342, and various kinds of actuator are housed inside the baseframe 308.

The main body frame 310 is formed of a resin material, and includes ahead portion frame 316 and a trunk portion frame 318. The head portionframe 316 is of a hollow hemispherical form, and forms a head portionframework of the robot 100. The trunk portion frame 318 is of a steppedcylindrical form, and forms a trunk portion framework of the robot 100.The trunk portion frame 318 is integrally fixed to the base frame 308.The head portion frame 316 is attached to an upper end portion of thetrunk portion frame 318 so as to be relatively displaceable.

Three shafts, those being a yaw shaft 320, a pitch shaft 322, and a rollshaft 324, and an actuator 326 for driving each shaft so as to rotate,are provided in the head portion frame 316. The actuator 326 includes amultiple of servo motors for driving each shaft individually. The yawshaft 320 is driven for a head shaking action, the pitch shaft 322 isdriven for a nodding action, and the roll shaft 324 is driven for a headtilting action.

A plate 325 that supports the yaw shaft 320 is fixed to an upper portionof the head portion frame 316. A multiple of ventilation holes 327 forsecuring ventilation between upper and lower portions are formed in theplate 325.

Abase plate 328 made of metal is provided so as to support the headportion frame 316 and an internal mechanism thereof from below. The baseplate 328 is linked to the plate 325 via a crosslink mechanism 329 (apantagraph mechanism), and is linked to the upper plate 332 (the baseframe 308) via a joint 330.

The trunk portion frame 318 houses the base frame 308 and a wheel drivemechanism 370. The wheel drive mechanism 370 includes a pivot shaft 378and an actuator 379. A lower half portion of the trunk portion frame 318is of a small width in order to form a housing space S of the frontwheel 102 between the wheel covers 312.

The outer skin 314 is formed of urethane rubber, and covers the mainbody frame 310 and the wheel covers 312 from an outer side. The arms 106are molded integrally with the outer skin 314. An aperture portion 390for introducing external air is provided in an upper end portion of theouter skin 314.

FIG. 3 is a configuration diagram of a robot system 300. The robotsystem 300 includes the robot 100, a server 200, and a multiple ofexternal sensors 114. The multiple of external sensors 114 (externalsensors 114 a, 114 b, and so on to 114 n) are installed in advance in ahouse. The external sensor 114 may be fixed to a wall surface of thehouse, or may be placed on a floor. Positional coordinates of theexternal sensor 114 are registered in the server 200. The positionalcoordinates are defined as x, y coordinates in the house envisaged to bean action range of the robot 100.

The server 200 is installed in the house. The server 200 and the robot100 in this embodiment correspond one-to-one. The server 200 determinesa basic action of the robot 100 based on information obtained from thesensors incorporated in the robot 100 and the multiple of externalsensors 114.

The external sensor 114 is for reinforcing sensory organs of the robot100, and the server 200 is for reinforcing brainpower of the robot 100.

The external sensor 114 regularly transmits a wireless signal (hereaftercalled a “robot search signal”) including ID (hereafter called “beaconID”) of the external sensor 114. On receiving the robot search signal,the robot 100 returns a wireless signal (hereafter called a “robotresponse signal”) including beacon ID. The server 200 measures a timefrom the external sensor 114 transmitting the robot search signal untilreceiving the robot response signal, and measures a distance from theexternal sensor 114 to the robot 100. By measuring the distance betweeneach of the multiple of external sensors 114 and the robot 100, theserver 200 identifies the positional coordinates of the robot 100.

Of course, a method whereby the robot 100 regularly transmits its ownpositional coordinates to the server 200 may also be adopted.

FIG. 4 is a schematic view of an emotion map 116.

The emotion map 116 is a data table stored in the server 200. The robot100 selects an action in accordance with the emotion map 116. Theemotion map 116 shown in FIG. 4 shows a magnitude of an emotionalattraction or aversion toward a place of the robot 100. An x axis and ay axis of the emotion map 116 indicate two-dimensional spatialcoordinates. A z axis indicates a magnitude of an emotional attractionor aversion. When a z value is a positive value, an attraction towardthe place is high, and when the z value is a negative value, the robot100 is averse to the place.

On the emotion map 116 of FIG. 4 , a coordinate P1 is a point in anindoor space managed by the server 200 as the action range of the robot100 at which an emotion of attraction is high (hereafter called afavored point). The favored point may be a “safe place”, such as behinda sofa or under a table, or may be a place in which people tend togather or a lively place, like a living room. Also, the safe place maybe a place where the robot 100 was gently stroked or touched in thepast.

A definition of what kind of place the robot 100 favors is arbitrary,but it is generally desirable that a place favored by small children, orby small animals such as dogs or cats, is set as a favored point.

A coordinate P2 is a point at which an emotion of aversion is high(hereafter called a “disliked point”). The disliked point may be a placewhere there is a loud noise, such as near a television, a place wherethere is likely to be a leak, like a bathroom or a washroom, an enclosedspace or a dark place, a place where the robot 100 has been roughlytreated by a user and that invokes an unpleasant memory, or the like.

A definition of what kind of place the robot 100 dislikes is alsoarbitrary, but it is generally desirable that a place feared by smallchildren, or by small animals such as dogs or cats, is set as a dislikedpoint.

A coordinate Q indicates a current position of the robot 100. The server200 identifies positional coordinates of the robot 100, using the robotsearch signal regularly transmitted by the multiple of external sensors114 and the robot response signal responding to the robot search signal.For example, when the external sensor 114 with beacon ID=1 and theexternal sensor 114 with beacon ID=2 each detect the robot 100, theserver 200 obtains the distances of the robot 100 from the two externalsensors 114, and obtains the positional coordinates of the robot 100from the distances.

Alternatively, the external sensor 114 with beacon ID=1 transmits therobot search signal in a multiple of directions, and the robot 100returns the robot response signal when receiving the robot searchsignal. By so doing, the server 200 may ascertain in which direction,and at what distance, the robot 100 is from which external sensor 114.Also, in another embodiment, the server 200 may calculate a distancemoved by the robot 100 from the rotational speed of the front wheel 102or the rear wheel 103, thereby identifying the current position, or mayidentify the current position based on an image obtained from thecamera.

When the emotion map 116 shown in FIG. 4 is provided, the robot 100moves in a direction toward the favored point (coordinate P1), or in adirection away from the disliked point (coordinate P2).

The emotion map 116 changes dynamically. When the robot 100 arrives atthe coordinate P1, the z value (emotion of attraction) at the coordinateP1 decreases with the passing of time. Because of this, the robot 100can emulate animal-like behavior of arriving at the favored point(coordinate P1), “being emotionally satisfied”, and in time “gettingbored” with the place. In the same way, the emotion of aversion at thecoordinate P2 is alleviated with the passing of time. A new favoredpoint or disliked point appears together with the elapse of time,because of which the robot 100 carries out a new action selection. Therobot 100 has “interest” in a new favored point, and ceaselessly carriesout a new action selection.

The emotion map 116 expresses emotional swings as an internal state ofthe robot 100. The robot 100 heads for a favored point, avoids adisliked point, stays for a while at the favored point, and in timeperforms the next action. With this kind of control, the actionselection of the robot 100 can be a human-like or animal-like actionselection.

Maps that affect an action of the robot 100 (hereafter collectivelycalled “action maps”) are not limited to the type of emotion map 116shown in FIG. 4 . For example, various action maps such as curiosity, adesire to avoid fear, a desire to seek safety, and a desire to seekphysical ease such as quietude, low light, coolness, or warmth, can bedefined. Further, an objective point of the robot 100 may be determinedby taking a weighted average of the z values of each of a multiple ofaction maps.

The robot 100 may also have, in addition to an action map, parametersthat indicate a magnitude of various emotions or senses. For example,when a value of a loneliness emotion parameter is increasing, aweighting coefficient of an action map that evaluates places in whichthe robot 100 feels at ease may be set high, and the value of thisemotion parameter reduced by the robot 100 reaching a target point. Inthe same way, when a value of a parameter indicating a sense of boredomis increasing, it is sufficient that a weighting coefficient of anaction map that evaluates places in which curiosity is satisfied is sethigh.

FIG. 5 is a hardware configuration diagram of the robot 100.

The robot 100 includes an internal sensor 128, a communicator 126, astorage device 124, a processor 122, a drive mechanism 120, and abattery 118. The drive mechanism 120 includes the heretofore describedwheel drive mechanism 370. The processor 122 and the storage device 124are included in the control circuit 342. The units are connected to eachother by a power line 130 and a signal line 132. The battery 118supplies power to each unit via the power line 130. Each unit transmitsand receives a control signal via the signal line 132. The battery 118is a lithium ion rechargeable battery, and is a power source of therobot 100.

The internal sensor 128 is a collection of various kinds of sensorincorporated in the robot 100. Specifically, the internal sensor 128 isa camera, a highly directional microphone, an infrared sensor, athermosensor, a touch sensor, an acceleration sensor, a smell sensor,and the like. The smell sensor is an already known sensor that applies aprinciple that electrical resistance changes in accordance with anadsorption of a molecule forming a source of a smell. The smell sensorclassifies various smells into multiple kinds of category (hereaftercalled “smell categories”).

The communicator 126 is a communication module that carries out wirelesscommunication with the server 200 and various kinds of external device,such as the external sensor 114 and a mobile device possessed by a user,as a target. The storage device 124 is configured of a non-volatilememory and a volatile memory, and stores a computer program and variouskinds of setting information. The processor 122 is means of executing acomputer program. The drive mechanism 120 is an actuator that controlsan internal mechanism. In addition to this, an indicator, a speaker, andthe like are also mounted.

The processor 122 selects an action of the robot 100 while communicatingwith the server 200 or the external sensor 114 via the communicator 126.Various kinds of external information obtained by the internal sensor128 also affect the action selection. The drive mechanism. 120 mainlycontrols the wheels (front wheels 102) and the head portion (the headportion frame 316). The drive mechanism 120 changes a direction ofmovement and a movement speed of the robot 100 by changing therotational speed and the direction of rotation of each of the two frontwheels 102. Also, the drive mechanism 120 can also raise and lower thewheels (the front wheels 102 and the rear wheel 103). When the wheelsrise, the wheels are completely stored in the body 104, and the robot100 comes into contact with the floor surface F via the seating face108, taking on the sitting state.

FIG. 6 is a functional block diagram of a robot system 300.

As heretofore described, the robot system 300 includes the robot 100,the server 200, and the multiple of external sensors 114. Each componentof the robot 100 and the server 200 is realized by hardware including acomputer formed of a CPU (central processing unit), various kinds ofcoprocessor, and the like, a storage device that is a memory or storage,and a wired or wireless communication line that links the computer andthe storage device, and software that is stored in the storage deviceand supplies a processing command to the computer. A computer programmay be configured of a device driver, an operating system, various kindsof application program positioned in an upper layer thereof, and alibrary that provides a common function to the programs. Each blockdescribed hereafter indicates a functional unit block rather than ahardware unit configuration.

One portion of the functions of the robot 100 may be realized by theserver 200, and one portion or all of the functions of the server 200may be realized by the robot 100.

Server 200

The server 200 includes a communication unit 204, a data processing unit202, and a data storage unit 206.

The communication unit 204 manages a process of communicating with theexternal sensor 114 and the robot 100. The data storage unit 206 storesvarious kinds of data. The data processing unit 202 executes variouskinds of process based on data acquired by the communication unit 204and data stored in the data storage unit 206. The data processing unit202 also functions as an interface of the communication unit 204 and thedata storage unit 206.

The data storage unit 206 includes a motion storage unit 232, a mapstorage unit 216, and an individual data storage unit 218.

The robot 100 has a multiple of operation patterns (motions). Variousmotions, such as waving the arm, approaching an owner while meandering,and staring at an owner with the head to one side, are defined.

The motion storage unit 232 stores control details of a motion (a motionfile). Each motion is identified by motion ID. The motion file is alsodownloaded into a motion storage unit 160 of the robot 100. Which motionis to be executed may be determined in the server 200, or may bedetermined in the robot 100.

Many motions of the robot 100 are configured as compound motions thatinclude a multiple of unit motions. For example, when the robot 100approaches an owner, the approach may be expressed as a combination of aunit motion of changing direction to face the owner, a unit motion ofapproaching while raising an arm, a unit motion of approaching whileshaking the body, and a unit motion of sitting while raising both arms.By combining these kinds of four motions, a motion of “approaching anowner, raising one arm on the way, and finally sitting after shaking thebody” is realized. An angle of rotation, angular velocity, and the likeof an actuator provided in the robot 100 is defined correlated to a timeaxis in a motion file. Various motions are performed by each actuatorbeing controlled together with the passing of time in accordance withthe motion file (actuator control information).

A shift time for changing from a preceding unit motion to a subsequentunit motion is called an “interval”. It is sufficient that an intervalis defined in accordance with time needed fora unit motion change ordetails of a motion. A length of an interval can be regulated.

Hereafter, settings involved in controlling an action of the robot 100,such as which motion is chosen and when, and output regulation of eachactuator when realizing a motion, will collectively be called“behavioral characteristics”. The behavioral characteristics of therobot 100 are defined by a motion selection algorithm, a motionselection probability, a motion file, and the like.

The map storage unit 216 stores a multiple of act ion maps. Theindividual data storage unit 218 stores information on a user, and inparticular, on an owner. Specifically, the individual data storage unit218 stores various kinds of parameter, such as familiarity with respectto a user, and physical characteristics and behavioral characteristicsof a user. The individual data storage unit 218 may also store otherattribute information such as age and gender.

The robot 100 identifies a user based on the user's physicalcharacteristics or behavioral characteristics. The robot 100 constantlyfilms a periphery using the incorporated camera. Further, the robot 100extracts the physical characteristics and behavioral characteristics ofa person appearing in an image. The physical characteristics may bevisual characteristics inherent to a body, such as a height, clothesworn by choice, a presence or absence of spectacles, a skin color, ahair color, or an ear size, or may also include other characteristicssuch as an average body temperature, a smell, and a voice quality. Thebehavioral characteristics, specifically, are characteristicsaccompanying behavior, such as a place the user favors, a briskness ofmovement, and a presence or absence of smoking. For example, the robot100 extracts behavioral characteristics such that an owner identified asa father is often out of the home, and is often motionless on a sofawhen at home, but a mother is often in a kitchen, and an activity rangeis broad.

The robot 100 clusters users appearing with a high frequency as “owners”based on physical characteristics and behavioral characteristicsobtained from a large amount of image information or other sensinginformation.

Although the method of identifying a user from user ID is simple andreliable, the user having a device that can provide user ID is aprecondition. Meanwhile, the method of identifying a user from physicalcharacteristics or behavioral characteristics is such that an imagerecognition process is weighty, but there is an advantage in that even auser who does not have a mobile device can be identified. One of the twomethods may be employed alone, or user identification may be carried outusing the two methods together in a complementary way.

In this embodiment, users are clustered based on physicalcharacteristics and behavioral characteristics, and a user is identifiedusing deep learning (a multilayer neural network). Details will bedescribed hereafter.

The robot 100 has a familiarity internal parameter for each user. Whenthe robot 100 recognizes an action indicating a liking toward the robot100, such as picking the robot 100 up or speaking to the robot 100,familiarity with respect to that user increases. Familiarity decreaseswith respect to a user not involved with the robot 100, a user whobehaves roughly, or a user met infrequently.

The data processing unit 202 includes a position managing unit 208, amap managing unit 210, a recognizing unit 212, an operation control unit222, a familiarity managing unit 220, a plan setting unit 240, and anactivity monitoring unit 242.

The position managing unit 208 identifies the positional coordinates ofthe robot 100 using a method relating to FIG. 3 . The position managingunit 208 may also track positional coordinates of a user in real time.

The map managing unit 210 changes the parameter of each coordinate onthe multiple of action maps using the method described in connectionwith FIG. 4 . The map managing unit 210 may select one of the multipleof action maps, or may take a weighted average of the z values of themultiple of action maps. For example, it is taken that the z values at acoordinate R1 and a coordinate R2 on an action map A are 4 and 3, andthe z values at the coordinate R1 and the coordinate R2 on an action mapB are −1 and 3. When taking a simple average, the total z value at thecoordinate R1 is 4−1=3, and the total z value at the coordinate R2 is3+3=6, because of which the robot 100 heads in the direction of thecoordinate R2 rather than the coordinate R1.

When the action map A is weighted 5 times with respect to the action mapB, the total z value at the coordinate R1 is 4×5−1=19, and the total zvalue at the coordinate R2 is 3×5+3=18, because of which the robot 100heads in the direction of the coordinate R1.

The recognizing unit 212 recognizes an external environment. Variouskinds of recognition, such as recognition of weather or season based ontemperature and humidity, and recognition of shelter (a safe area) basedon an amount of light and temperature, are included in the recognitionof the external environment. The recognizing unit 212 further includes aperson recognizing unit 214 and a response recognizing unit 228. Theperson recognizing unit 214 recognizes a person from an image filmed bythe camera incorporated in the robot 100, and extracts the physicalcharacteristics and behavioral characteristics of the person. Further,based on the physical characteristic information and behavioralcharacteristic information registered in the individual data storageunit 218, the person recognizing unit 214 determines what person, suchas a father, a mother, or an eldest son, the user filmed, that is, theuser the robot 100 is looking at, corresponds to. The person recognizingunit 214 includes an expression recognizing unit 230. The expressionrecognizing unit 230 infers an emotion of a user using image recognitionof an expression of the user.

The person recognizing unit 214 also extracts characteristics of amoving object other than a person, for example, a cat or a dog that is apet.

The response recognizing unit 228 recognizes various responsive actionsperformed with respect to the robot 100, and classifies the actions aspleasant or unpleasant actions. Also, the response recognizing unit 228recognizes a responsive action of an owner with respect to an action ofthe robot 100, thereby classifying the responsive action as a positiveor negative response.

Pleasant and unpleasant actions are distinguished depending on whether aresponsive action of a user is pleasing or unpleasant for an animal. Forexample, being hugged is a pleasant action for the robot 100, and beingkicked is an unpleasant action for the robot 100. Positive and negativeresponses are distinguished depending on whether a responsive action ofa user indicates a pleasant emotion or an unpleasant emotion of theuser. For example, being hugged is a positive response indicating apleasant emotion of the user, and being kicked is a negative responseindicating an unpleasant emotion of the user.

The operation control unit 222 of the server 200 determines a motion ofthe robot 100 in cooperation with an operation control unit 150 of therobot 100. The operation control unit 222 of the server 200 compiles amovement target point of the robot 100, and a movement route for themovement target point, based on an action map selection by the mapmanaging unit 210. The movement control unit 222 compiles a multiple ofmovement routes, and having done so, may select any of the movementroutes.

The operation control unit 222 selects a motion of the robot 100 from amultiple of motions of the motion storage unit 232. A selectionprobability is correlated for each situation to each motion. Forexample, a selection method such that a motion A is executed at aprobability of 20% when a pleasant action is performed by an owner, anda motion B is executed at a probability of 5% when an air temperature is30 degrees or higher, is defined.

A movement target point and a movement route are determined by an actionmap, and a motion is selected in accordance with various kinds of eventto be described hereafter.

The familiarity managing unit 220 manages familiarity for each user. Asheretofore described, familiarity is registered as one portion ofindividual data in the individual data storage unit 218. When a pleasantaction is detected, the familiarity managing unit 220 increasesfamiliarity with respect to that owner. When an unpleasant action isdetected, the familiarity managing unit 220 reduces familiarity. Also,familiarity of an owner not visually recognized for a long periodgradually decreases.

The plan setting unit 240 sets “consumption plan data”. Consumption plandata define a power consumption pace of the battery 118. For example, ina case of consumption plan data for one hour (hereafter written as a“one hour plan”), a remaining charge of the battery 118 reaches a lowerlimit value after one hour of activity. In a case of a three hour plan,the remaining battery charge reaches the lower limit value after threehours of activity. As the power consumption pace of the three hour planis slow compared with that of the one hour plan, the activity time islonger. In exchange for this, an activity amount per unit time of therobot 100 is restricted. Details of consumption plan data will bedescribed hereafter.

The activity monitoring unit 242 records an operation history of therobot 100. Motion selections and positional coordinates of the robot 100are recorded chronologically in the operation history. Various events,such as who the robot 100 met at what timing, and what kind ofresponsive action has been detected, are also recorded.

Robot 100

The robot 100 includes a communication unit 142, a data processing unit136, a data storage unit 148, the battery 118, and the drive mechanism120.

The communication unit 142 corresponds to the communicator 126 (refer toFIG. 5 ), and manages a process of communicating with the externalsensor 114 and the server 200. The data storage unit 148 stores variouskinds of data. The data storage unit 148 corresponds to the storagedevice 124 (refer to FIG. 5 ). The data processing unit 136 executesvarious kinds of process based on data acquired by the communicationunit 142 and data stored in the data storage unit 148. The dataprocessing unit 136 corresponds to the processor 122 and a computerprogram executed by the processor 122. The data processing unit 136 alsofunctions as an interface of the communication unit 142, the internalsensor 128, the drive mechanism 120, and the data storage unit 148.

The data storage unit 148 includes the motion storage unit 160, whichdefines various kinds of motion of the robot 100.

Various kinds of motion file are downloaded into the motion storage unit160 of the robot 100 from the motion storage unit 232 of the server 200.A motion is identified by motion ID. An operating timing, an operatingtime, an operating direction, and the like, of the various kinds ofactuator (the drive mechanism 120) are defined chronologically in amotion file in order to perform various motions such as sitting byhousing the front wheel 102, raising the arm 106, causing the robot 100to carry out a rotating action by causing the two front wheels 102 torotate in reverse or by causing only one front wheel 102 to rotate,shaking by causing the front wheel 102 to rotate in a state in which thefront wheel 102 is housed, or stopping once and looking back when movingaway from a user.

The data processing unit 136 includes a recognizing unit 156, theoperation control unit 150, and a remaining battery charge monitoringunit 172.

The operation control unit 150 of the robot 100 determines motions ofthe robot 100 in cooperation with the operation control unit 222 of theserver 200. One portion of motions may be determined by the server 200,and other motions may be determined by the robot 100. Also, aconfiguration may be such that although the robot 100 determinesmotions, the server 200 determines a motion when a processing load ofthe robot 100 is high. A configuration may be such that a motion forminga base is determined by the server 200, and an additional motion isdetermined by the robot 100. It is sufficient that the way a motiondetermining process is divided between the server 200 and the robot 100is designed in accordance with specifications of the robot system 300.

The operation control unit 150 of the robot 100 determines a directionof movement of the robot 100 together with the operation control unit222 of the server 200. Movement based on an action map may be determinedby the server 200, and an immediate movement such as avoiding anobstacle may be determined by the operation control unit 150 of therobot 100. The drive mechanism 120 causes the robot 100 to head toward amovement target point by driving the front wheel 102 in accordance withan instruction from the operation control unit 150.

The operation control unit 150 of the robot 100 instructs the drivemechanism 120 to execute a selected motion. The drive mechanism 120controls each actuator in accordance with the motion file.

The operation control unit 150 can also execute a motion of holding upboth arms 106 as a gesture asking for “a hug” when a user with a highdegree of familiarity is nearby, and can also perform a motion of nolonger wanting to be hugged by repeatedly causing the left and rightfront wheels 102 to alternately rotate in reverse and stop in a housedstate when bored of the “hug”. The drive mechanism 120 causes the robot100 to perform various motions by driving the front wheel 102, the arm106, and the neck (head portion frame 316) in accordance with aninstruction from the operation control unit 150.

The remaining battery charge monitoring unit 172 monitors the remainingcharge of the battery 118. The remaining battery charge varies between 0and 100%. Details will be described hereafter, but when the remainingbattery charge reaches a lower limit value, 20% for example, theoperation control unit 222 causes the robot 100 to head toward acharger. Also, when the remaining battery charge reaches an upper limitvalue, 80% for example, the operation control unit 222 issues aninstruction to move away from the charger.

The recognizing unit 156 (a target detecting unit) of the robot 100analyzes external information obtained from the internal sensor 128. Therecognizing unit 156 is capable of visual recognition (a visual unit),smell recognition (an olfactory unit), sound recognition (an auralunit), and tactile recognition (a tactile unit).

The recognizing unit 156 regularly films an exterior angle using theincorporated camera (the internal sensor 128), and detects a movingobject such as a person or a pet. Characteristics thereof aretransmitted to the server 200, and the person recognizing unit 214 ofthe server 200 extracts the physical characteristics of the movingobject. Also, the recognizing unit 156 also detects a smell of the userand a voice of the user. Smell and sound (voice) are classified intomultiple kinds using an already known method.

When a strong force is applied to the robot 100, the recognizing unit156 recognizes this using an incorporated acceleration sensor, and theresponse recognizing unit 228 of the server 200 recognizes that a“violent action” has been performed by a user in the vicinity. When auser picks the robot 100 up by grabbing the horn 112, this may also berecognized as a violent action. When a user in a state of confrontingthe robot 100 speaks in a specific volume region and a specificfrequency band, the response recognizing unit 228 of the server 200 mayrecognize that a “speaking action” has been performed with respect tothe robot 100. Also, when a temperature in the region of bodytemperature is detected, the response recognizing unit 228 of the server200 recognizes that a “touching action” has been performed by a user,and when upward acceleration is detected in a state in which touching isrecognized, the response recognizing unit 228 of the server 200recognizes that a “hug” has been performed. Physical contact when a userraises the body 104 may also be sensed, and a hug may also be recognizedby a load acting on the front wheels 102 decreasing.

The response recognizing unit 228 of the server 200 recognizes variouskinds of response by a user toward the robot 100. “Pleasant” or“unpleasant”, “positive” or “negative” is correlated to one portion oftypical responsive actions among various kinds of responsive action. Ingeneral, almost all responsive actions that are pleasant actions arepositive responses, and almost all responsive actions that areunpleasant actions are negative responses. Pleasant and unpleasantactions relate to familiarity, and positive and negative responsesaffect action selection of the robot 100.

A series of recognition processes including detecting, analyzing, anddetermining may be carried out by the recognizing unit 212 of the server200 alone, or carried out by the recognizing unit 156 of the robot 100alone, or the two may execute the recognition processes while dividingroles.

The familiarity managing unit 220 of the server 200 changes thefamiliarity toward a user in accordance with a responsive actionrecognized by the recognizing unit 156. Essentially, the familiaritytoward a user who carries out a pleasant action increases, while thefamiliarity toward a user who carries out an unpleasant actiondecreases.

The recognizing unit 212 of the server 200 may determine whether aresponse is pleasant or unpleasant, and the map managing unit 210 of theserver 200 may change the z value of the point at which the pleasant orunpleasant action has been carried out on an action map that represents“attachment to a place”. For example, when a pleasant action is carriedout in a living room, the map managing unit 210 may set a favored pointat a high probability in the living room. In this case, a positivefeedback advantage is realized in that the robot 100 favors the livingroom, and further favors the living room due to being the recipient of apleasant action in the living room.

The person recognizing unit 214 of the server 200 detects a movingobject from various kinds of data obtained from the external sensor 114or the internal sensor 128, and extracts characteristics (physicalcharacteristics and behavioral characteristics) thereof. Further, theperson recognizing unit 214 cluster analyzes multiple moving objectsbased on these characteristics. Not only a human, but also a pet such asa dog or cat, may be a target of analysis as a moving object.

The robot 100 regularly carries out image filming, and the personrecognizing unit 214 recognizes a moving object from the images, andextracts characteristics of the moving object. When a moving object isdetected, physical characteristics and behavioral characteristics arealso extracted from the smell sensor, the incorporated highlydirectional microphone, the temperature sensor, and the like. Forexample, when a moving object appears in an image, variouscharacteristics are extracted, such as having a beard, being activeearly in the morning, wearing red clothing, smelling of perfume, havinga loud voice, wearing spectacles, wearing a skirt, having white hair,being tall, being plump, being suntanned, or being on a sofa.

When a moving object (user) having a beard is often active early in themorning (gets up early) and rarely wears red clothing, a first profilethat is a cluster (user) that gets up early, has a beard, and does notoften wear red clothing is created. Meanwhile, when a moving objectwearing spectacles often wears a skirt, but the moving object does nothave a beard, a second profile that is a cluster (user) that wearsspectacles and wears a skirt, but definitely does not have a beard, iscreated.

Although the above is a simple example, the first profile correspondingto a father and the second profile corresponding to a mother are formedusing the heretofore described method, and the robot 100 recognizes thatthere at least two users (owners) in this house.

Note that the robot 100 does not need to recognize that the firstprofile is the “father”. In all cases, it is sufficient that the robot100 can recognize a figure that is “a cluster that has a beard, oftengets up early, and hardly ever wears red clothing”.

It is assumed that the robot 100 newly recognizes a moving object (user)in a state in which this kind of cluster analysis is completed.

At this time, the person recognizing unit 214 of the server 200 extractscharacteristics from sensing information of an image or the likeobtained from the robot 100, and determines which cluster a movingobject near the robot 100 corresponds to using deep learning (amultilayer neural network). For example, when a moving object that has abeard is detected, the probability of the moving object being the fatheris high. When the moving object is active early in the morning, it isstill more certain that the moving object corresponds to the father.Meanwhile, when a moving object that wears spectacles is detected, thereis a possibility of the moving object being the mother. When the movingobject has a beard, the moving object is neither the mother nor thefather, because of which the person recognizing unit 214 determines thatthe moving object is a new person who has not been cluster analyzed.

Formation of a cluster by characteristic extraction (cluster analysis)and application to a cluster accompanying characteristic extraction(deep learning) may be executed concurrently.

Familiarity toward a moving object (user) changes in accordance with howthe robot 100 is treated by the user.

The robot 100 sets a high familiarity for a frequently met person, aperson who frequently touches the robot 100, and a person who frequentlyspeaks to the robot 100. Meanwhile, familiarity decreases for a rarelyseen person, a person who does not often touch the robot 100, a violentperson, and a person who scolds in a loud voice. The robot 100 changesthe familiarity of each user based on various items of exterior angleinformation detected by the sensors (visual, tactile, and aural).

The actual robot 100 autonomously carries out a complex action selectionin accordance with an action map. The robot 100 acts while beingaffected by a multiple of action maps based on various parameters suchas loneliness, boredom, and curiosity. When the effect of the actionmaps is removed, or when in an internal state in which the effect of theaction maps is small, the robot 100 essentially attempts to approach aperson with high familiarity, and attempts to move away from a personwith low familiarity.

Actions of the robot 100 are classified below in accordance withfamiliarity.

(1) A cluster with extremely high familiarity

The robot 100 strongly expresses a feeling of affection by approaching auser (hereafter called “an approaching action”), and by performing anaffectionate gesture defined in advance as a gesture indicating goodwilltoward a person.

(2) A cluster with comparatively high familiarity

The robot 100 carries out only an approaching action.

(3) A cluster with comparatively low familiarity

The robot 100 does not carry out any special action.

(4) A cluster with particularly low familiarity

The robot 100 carries out a withdrawing action.

According to the heretofore described control method, the robot 100approaches the user when finding a user with high familiarity, andconversely, moves away from the user when finding a user with lowfamiliarity. According to this kind of control method, the robot 100 canexpress by behavior a so-called “shyness”. Also, when a visitor (a userA with low familiarity) appears, the robot 100 may move away from thevisitor and head toward a family member (a user B with highfamiliarity). In this case, user B can perceive that the robot 100 isshy and feeling uneasy, and relying on user B. Owing to this kind ofbehavioral expression, pleasure at being chosen and relied upon, and anaccompanying feeling of affection, are evoked in user B.

Meanwhile, when user A, who is a visitor, visits frequently, and speaksto and touches the robot 100, familiarity of the robot 100 toward user Agradually rises, and the robot 100 ceases to perform an action ofshyness (a withdrawing action) with respect to user A. User A can alsofeel affection toward the robot 100 by perceiving that the robot 100 hasbecome accustomed to user A.

The heretofore described action selection need not necessarily beexecuted constantly. For example, when an internal parameter indicatingcuriosity of the robot 100 is high, weight is given to an action mapfrom which a place in which the curiosity is satisfied is obtained,because of which there is also a possibility that the robot 100 does notselect an action affected by familiarity. Also, when the external sensor114 installed in the hall detects the return home of a user, the robot100 may execute an action of greeting the user with maximum priority.

FIG. 7 is a data structure diagram of a load table 170.

Motions selected by the operation control unit 222 of the server 200 andthe operation control unit 150 of the robot 100 have various processingloads. Herein, a processing load is a concept indicating a motionexecution cost, and is defined by, for example, a number of unit motionsincluded in one motion, a complexity of a motion, a number of actuatorsused for executing a motion, an operating amount of an actuator, amotion execution time, power consumption (energy) for executing amotion, and the like. A motion with a large processing load (hereaftercalled a “high-load motion”) is often an energetic motion, and a motionwith a small processing load (hereafter called a “low-load motion”) isoften a low-key motion.

Complex motions such as, for example, rotating while shaking the head ormeandering at high speed are included as high-load motions. Simplemotions such as, for example, nodding or sitting are included aslow-load motions.

In this embodiment, an evaluation value (hereafter called a “loadvalue”) is set in advance within a range of 1 to 100 for the processingload of each motion. The load value may be set by a designer of themotion, or may be set based on an actual measurement value of powerconsumption or the like.

The load table 170 defines a correspondence relationship between amotion and a processing load (load value). The load table 170 is storedin both the motion storage unit 232 of the server 200 and the motionstorage unit 160 of the robot 100. The operation control unit 222 andthe like refer to the load table 170, and select a motion using a methodto be described hereafter.

According to FIG. 7 , the load value, that is, the evaluation value ofthe magnitude of the processing load, of a motion with motion ID=C01(hereafter written as a “motion (C01)”) is set at “20”. Meanwhile, theload value of a motion (C02) is “10”. This means that the motion (C01)requires twice the energy of the motion (C02). An amount of powerconsumed per unit time varies in accordance with which motion isselected.

FIG. 8 is a data structure diagram of a motion selection table 180.

The motion selection table 180 defines a motion to be executed whenvarious kinds of event occur. When an event occurs, the robot 100selects one or more motions from multiple kinds of motion. The motionselection table 180 is stored in both the motion storage unit 232 of theserver 200 and the motion storage unit 160 of the robot 100. An “event”is defined in advance as a phenomenon that forms a trigger for the robot100 to execute a motion. Details of an event are arbitrary, such as whenvisually recognizing an owner, when being hugged by an owner, when beingkicked, or when not visually recognizing anyone for a predetermined timeor longer.

When referring to FIG. 8 , a selection probability is correlated to eachof the motion (C01) to a motion (Cx) for an event J1. For example, whenthe event J1 occurs, the operation control unit 222 does not select themotion (C01), and selects the motion (C02) at a probability of 0.1%.When an event J2 occurs, the operation control unit 222 selects themotion (C01) at a probability of 0.1%, and selects the motion (C02) at aprobability of 0.4%.

A selection probability in the motion selection table 180 is not a fixedvalue. The operation control unit 222 causes the selection probabilityto change as necessary in accordance with the remaining charge of thebattery 118, or the like. When a selection probability of the motionselection table 180 is updated, the motion selection table 180 afterupdating is downloaded into the robot 100.

For example, the selection probability of the high-load motion (C01) maydecrease by half when the remaining battery charge reaches 50% or less,and the selection probability of the motion (C01) may further decreaseby half when the remaining battery charge reaches 30% or less.Meanwhile, the selection probability of the low-load motion (C04) mayincrease by 1.2 times when the remaining battery charge reaches 50% orless, and the selection probability thereof may further increase by 1.2times when the remaining battery charge reaches 30% or less.

By refraining more from executing a high-load motion the lower theremaining battery charge becomes, the activity time of the robot 100 canbe extended. Even when no special event is occurring, the operationcontrol unit 222 may select a motion at a predetermined selectionprobability. In this case too, the operation control unit 222 causes theselection probability of the motion to change in accordance with theremaining battery charge. According to this kind of control method,behavioral characteristics such that the robot 100 is active when theremaining battery charge is large, and becomes quiet when the remainingbattery charge becomes small, can be expressed.

The operation control unit 222 may select a high-load motion when theremaining battery charge is small. For example, the selectionprobability of the high-load motion (C01) may be temporarily increasedby 3 times while an SOC is between 35 and 40%. This kind of control issuch that, while being affected by the remaining battery charge,unexpected behavioral characteristics that do not depend only on theremaining battery charge can be expressed.

It is assumed that there are certain two motions, one thereof is acomparatively high-load motion, and the other is a comparativelylow-load motion. It is assumed that the selection probability of thehigh-load motion is Y1, and the selection probability of the low-loadmotion is Y2. It is assumed that Y1/Y2=p. When the remaining batterycharge drops to or below a certain threshold, p is desirably smallercompared with when the remaining battery charge is greater than thethreshold. It is sufficient, at least in statistical terms, that whenthe remaining battery charge is small, the selection probability of thehigh-load motion decreases, or that the selection probability of thelow-load motion rises, in comparison with when that is not the case.

An event such that the selection probability is not affected by theremaining battery charge (hereafter referred to as a priority event) maybe defined. It is sufficient that a priority event is defined as anevent such that an action is of high importance, such as an ownerreturning home or leaving home or a state of emergency such as a robberor a fire. A configuration may be such that when a priority eventoccurs, the operation control unit 222 need not cause the selectionprobability of one or more motions correlated to the priority event tochange in accordance with the remaining battery charge, or may alwaysexecute a specific motion when the priority event occurs.

The selection probability of a motion may be changed in accordance withan absolute value of the remaining battery charge, but in thisembodiment, the selection probability of a motion is changed inaccordance with a value of a difference between consumption plan dataand the remaining battery charge. Next, consumption plan data will bedescribed.

FIG. 9 is a schematic diagram showing a relationship between consumptionplan data and motion selection.

As heretofore described, the plan setting unit 240 sets consumption plandata that establish a power consumption pace. When the remaining batterycharge decreases to or below a lower limit value E1, the operationcontrol unit 222 causes the robot 100 to move to a charger, and to becharged. When the remaining battery charge reaches an upper limit valueE2 (>E1) or greater, the operation control unit 222 causes the robot 100to move away from the charger. In this way, when the remaining charge ofthe battery 118 is within the range of E1 to E2, the robot 100 is activedistanced from the charger. In other words, a period for which theremaining charge of the battery 118 is within the range of E1 to E2 isthe activity time of the robot 100.

A one-hour plan 182 is a plan such that power is consumed from the upperlimit value E2 to the lower limit value E1 in one hour after charging iscompleted. A three-hour plan 184 is a plan such that the power isconsumed in three hours. The one-hour plan 182 is such that aftercharging is completed, the remaining battery charge 0.5 hours later isF2, and the remaining battery charge reaches the lower limit value E2one hour later. The activity time of the robot 100 is one hour.Meanwhile, the three-hour plan 184 is such that after charging iscompleted, the remaining battery charge 0.5 hours later is F3 (>F2), andthe remaining battery charge reaches the lower limit value E2 threehours later. The activity time of the robot 100 is three hours.

The power consumption pace does not need to be constant in theconsumption plan. For example, the power consumption pace may be set tobe low at first, and the power consumption pace may be raised partwaythrough. A consumption plan selection reference will be describedhereafter.

A remaining battery charge graph line 186 indicates an actual powerconsumption pace. When the one-hour plan 182 is being employed, theremaining battery charge graph line 186 is such that the powerconsumption pace is gentle when compared with the one-hour plan 182. Inthis case, the operation control unit 222 raises the selectionprobability of a high-load motion. For example, a difference between thescheduled value F2 of the remaining battery charge and an actualremaining battery charge value F1 0.5 hours after charging is completedis calculated, and when the value of the difference is equal to orgreater than a predetermined threshold, the operation control unit 222changes the selection probability of the high-load motion (C01) to betwice as high. Not being limited to the motion (C01), it is sufficientthat the selection probability of a high-load motion is raised, and theselection probability of a low-load motion is reduced. Owing to thiskind of setting change, a high-load motion becomes easy to select and alow-load motion becomes difficult to select, because of which thedifference between the one-hour plan 182 and the remaining batterycharge graph line 186 can be reduced. That is, power consumption inaccordance with the one-hour plan 182 is realized by encouragingenergetic behavior for the robot 100.

When the three-hour plan 184 is being employed, the remaining batterycharge graph line 186 is such that the power consumption pace is toofast when compared with the three-hour plan 184. In this case, theoperation control unit 222 reduces the selection probability of ahigh-load motion. A difference between the scheduled value F2 of theremaining battery charge and the actual remaining battery charge valueF3 0.5 hours after charging is completed is calculated, and theoperation control unit 222 may reduce the selection probability of thehigh-load motion (C01) by half in order to eliminate the difference ofF3−F2. Not being limited to the motion (C01), it is sufficient that theselection probability of a high-load motion is reduced, and theselection probability of a low-load motion is raised. By this kind ofsetting change being carried out, a high-load motion becomes difficultto select and a low-load motion becomes easy to select. By restrictingthe activity amount of the robot 100, power consumption in accordancewith the three-hour plan 184 is realized.

According to the heretofore described control method, energetic behavioris easily selected in exchange for the activity time of the robot 100being short when the one-hour plan 182 is set, and when the three-hourplan 184 is set, the robot 100 becomes quiet but the activity timeincreases. Consequently, activity of the robot 100 can be controlled inaccordance with a selection of consumption plan data. Also, there isalso an advantage in that power consumption of the robot 100 can bemanaged using consumption plan data.

FIG. 10 is a schematic diagram of a consumption plan selection table188.

The activity monitoring unit 242 records the operation history of therobot 100. Further, the activity monitoring unit 242 calculates anactivity amount per unit time. For example, when the motion (C01), themotion (C02), and the motion (C03) are executed in a certain unit time,a total load value in this time is 33 (=20+10+3: refer to FIG. 7 ). Theconsumption plan selection table 188 defines a total load value as an“activity amount”, and sets a correspondence between the activity amountand consumption plan data.

According to the consumption plan selection table 188, the plan settingunit 240 selects a consumption plan (D01) when the activity amount is200 or greater, and when the activity amount is 160 or greater and lessthan 200, the plan setting unit 240 selects a consumption plan (D02).For example, when charging is completed at 3.10 p.m., the plan settingunit 240 obtains an average value of the activity amount from 3.10 p.m.to 4.10 p.m. from a past operation history. Then, when the averageactivity amount for the one hour from 3.10 p.m. to 4.10 p.m. for thepast 10 days is 155, the plan setting unit 240 selects a consumptionplan (D03).

For a time band in which the activity amount is large, the plan settingunit 240 sets consumption plan data such that the activity time is shortin exchange for the activity amount being large, and for a time band inwhich the activity amount is small, the plan setting unit 240 setsconsumption plan data such that the activity time is long in exchangefor the activity amount being small. In the case of FIG. 10 , theconsumption plan (D01) has the shortest activity time, and a consumptionplan (D07) has the longest activity time.

When a consumption plan with a short activity time is selected, therobot 100 behaves energetically. Also, the more the robot 100 interactswith an owner, the more the activity amount is liable to increase. Thisis because various events are set corresponding to responsive actions byan owner. The more frequently an event occurs, the greater the number ofmotion selections. In particular, the robot 100 reacts in a largevariety of ways to a positive interaction such as contact with the robot100.

The robot 100 behaves energetically when an owner is present, andparticularly when a large number of owners are present, and in a timeband in which there is a large activity amount, consumption plan dataresponding thereto are selected. Also, consumption plan data such thatthe power consumption pace is gentle are selected in a time band inwhich there is a small activity amount. The robot 100 becomes quiet in atime band in which nobody is watching the robot 100, and in a time bandin which nobody is actively involved with the robot 100, and the robot100 behaves energetically, bringing enjoyment to the owners, in a timeband in which the robot 100 attracts attention.

The robot 100 restricting activity in a time band in which the robot 100does not attract attention is thoughtful behavior in terms of notgetting in the way of an owner, and also contributes to power saving.The robot 100 selects various motions in response to events such asvisually recognizing an owner, contact, and being spoken to. When therecognizing unit 156 of the robot 100 detects a moving object such as anowner or a pet, the selection probability of an energetic motion, or inother words, a high-load motion, is raised, and the selectionprobability of a low-load motion is reduced. It is sufficient that asetting change is carried out so that of at least two motions, the ratioof the selection probability of a high-load motion with respect to theselection probability of a low-load motion increases.

The activity amount may be calculated from the load value of eachmotion, or may be calculated from an amount of power consumed per unittime.

Although an activity amount and a consumption plan are correlated in theconsumption plan selection table 188, a time band and a consumption planmay also be correlated. According to this kind of setting method, forexample, an activity amount in a time band such that the robot 100 isquiet in the morning and energetic at night can be controlled using theconsumption plan selection table 188. Also, the operation control unit222 may set a charging timing, such as always charging in the middle ofthe night.

FIG. 11 is a schematic diagram showing a relationship between processingload and selection probability.

Non-patent Document 1 reveals that a result of measuring human activityusing a wearable sensor shows that there is a statistical regularity tohuman behavior selection (refer to P27 of Non-patent Document 1).Measuring a number of physical movements of a human per minute showsthat there is a large amount of time in which movement is calm, such as50 times/minute, and an extremely small amount of time in which violentmovement is performed. Further, it is said that a stable relationshipbetween violence of movement and a probability of selecting such amovement is found. A human thinks that he or she is deciding on his orher own behavior freely by his or her own will or thinking, but there isa strange regularity to an accumulation of the behavior selections. Itmight be that behavioral characteristics that accord with this kind ofregularity can be said to be “animal-like behavioral characteristics”.

By this kind of regularity being applied to motion selection, thebehavioral characteristics of the robot 100 in this embodiment arerendered still more “animal-like”.

In FIG. 7 , a vertical axis is a logarithmic axis, and shows anaccumulative selection probability. A horizontal axis is a processingload of each motion. A basic activity graph line 190 indicates arelationship between a motion and the selection probability(accumulative probability) thereof. According to the basic activitygraph line 190, a time band in which a motion with a processing load ofG1 or greater is executed is shown to be ⅛ of one day. In other words,only a motion with a processing load of less than G1 is selected for ⅞of one day. Expressed simply, a high-load motion is unlikely to beselected, and a low-load motion is likely to be selected.

As heretofore described, the operation control unit 222 selects a motionof the robot 100 in response to various events. Which of a multiple ofmotions is to be selected is determined in accordance with the motionselection table 180. A selection probability in the motion selectiontable 180 is not a fixed value. The operation control unit 222 changes aselection probability in the motion selection table 180 as appropriatein accordance with the remaining battery charge, or more precisely, inaccordance with a result of comparing the remaining battery charge andthe consumption plan. When the actual remaining battery charge and thescheduled value in the consumption plan are distanced, the operationcontrol unit 222 changes the selection probability in order to eliminatethe distance. Furthermore, the change method accords with the regularityof the basic activity graph line 190 shown in FIG. 11 .

For example, when there is more leeway in the remaining battery chargethan in the scheduled value of the consumption plan, the operationcontrol unit 222 increases the selection probability of a high-loadmotion, or in other words, an energetic motion. At this time, theoperation control unit 222 changes a selection from the basic activitygraph line 190 to a high activity graph line 192, and changes theselection probability of each motion so as to correspond to the highactivity graph line 192. The high activity graph line 192 is also suchthat linearity is maintained, because of which animal-like and naturalbehavioral characteristics can be maintained. In the high activity graphline 192, a time band in which a motion with a processing load of G2(>G1) or greater is executed is ⅛ of one day. The activity amountincreases compared with that of the basic activity graph line 190.

Meanwhile, when the remaining battery charge is less than the scheduledvalue of the consumption plan, the operation control unit 222 reducesthe selection probability of a high-load motion. The operation controlunit 222 changes a setting from the basic activity graph line 190 to alow activity graph line 194, and changes the selection probability ofeach motion so as to correspond to the low activity graph line 194. Inthe low activity graph line 194, a time band in which a motion with aprocessing load of G3 (<G1) or greater is executed is ⅛ of one day. Theactivity amount decreases compared with that of the basic activity graphline 190.

The activity monitoring unit 242 refers to the operation history, andcounts which events are occurring how many times a day. The activitymonitoring unit 242 calculates by simulation a number of times eachmotion is selected per day, based on a probability of each eventoccurring and the selection probability of each motion correlated to theevent. For example, it is assumed that an event A occurs an average of10 times per day, and an event B occurs an average of 7 times per day.It is assumed that the selection probability of a motion X responding tothe event A is 5%, and the selection probability of the motion Xresponding to the event B is 10%. In this case, the number of selectionsper day of the motion X is 1.2 (=10×0.05+7×0.10) times. The number ofselections of each motion is calculated in the same way.

Next, the number of selections of each motion and the basic activitygraph line 190 are compared, and the selection probability of eachmotion is obtained, using an already known optimization method such asthe Monte Carlo method, so as to obtain a selection probabilitydistribution that coincides with the basic activity graph line 190. Inthe same way, selection probability distributions corresponding to thehigh activity graph line 192 and the low activity graph line 194 areset. It is sufficient that selection probability sets of motion groupscorresponding to the basic activity graph line 190, the high activitygraph line 192, and the low activity graph line 194 are prepared inadvance, and the basic activity graph line 190, the high activity graphline 192, or the low activity graph line 194 is selected while comparingthe consumption plan and the remaining battery charge.

According to the heretofore described control method, motion selectionbased on the animal-like regularity shown in FIG. 11 and motionselection based on the consumption plan can be balanced.

FIG. 12 is a flowchart showing a process when a priority event occursduring charging.

When charging is not in progress (N of S10), a subsequent process isskipped. When charging is in progress (Y of S10) and the charging iscompleted (Y of S12), the operation control unit 222 causes the robot100 to move away from the charger (S14). Charging being completed iswhen the remaining battery charge exceeds the upper limit value E2(refer to FIG. 9 ).

When a priority event occurs (Y of S16) when charging is not completed(N of S12), the robot 100 selects a motion correlated to the priorityevent (S18). Meanwhile, when no event is occurring, or when an eventthat occurs is not a priority event (N of S16), charging is continued.

As heretofore described, a priority event is an important event such asan owner returning home or leaving home. When the external sensor 114installed in a hall detects a person in a monitoring area of theexternal sensor 114, the robot 100 moves to the hall and performs agreeting. Having once entered a charging mode, the robot 100 does notmove, but when an important phenomenon such as an owner returning homeoccurs, the robot 100 executes a greeting action even though charging isnot completed.

When a priority event occurs, the operation control unit 222 carries outa selection of a motion responding to the priority event, regardless ofwhether charging is in progress or not, or whether the remaining batterycharge is large or small. Behavioral characteristics that respondprecisely to the priority event are realized, without being excessivelyregulated by the remaining battery charge.

Even when a return home is detected, whether or not this is to be seenas a priority event may be determined in accordance with the familiarityof the person detected. For example, when an owner with a familiarity ofa predetermined threshold or greater returns home, the operation controlunit 222 sees this as a priority event, and issues an instruction for agreeting action. Meanwhile, when an owner with a familiarity of lessthan the predetermined threshold returns home, the operation controlunit 222 need not see this as a priority event.

Hereafter, the robot 100 and the robot system 300 including the robot100 will be described, based on an embodiment.

The robot 100 performs an action selection that cannot be patternedusing one or more action maps, and which is difficult to predict andanimal-like.

In the same way as a living creature, the behavior of the robot 100changes in accordance with not only an action map, but also variouskinds of event. According to this embodiment, the robot 100 actsenergetically when the remaining battery charge is large. Meanwhile, therobot 100 becomes quiet when the remaining battery charge decreases.Because of this, behavior indicating that the remaining battery chargeforms a source of vitality of the robot 100 can be expressed. Animpression close to that of sleeping or eating can be given to themechanical process of charging.

By the activity amount of the robot 100 being controlled in accordancewith the consumption plan data, a time band in which the robot 100 is tobe active and a time band in which the robot 100 is to be quiet can becontrolled. This also contributes to saving power of the robot 100.

Sleeping and eating are necessary in order for a human to move. When animportant phenomenon occurs, a human acts even when sleeping or eating,or even when tired due to a lack of sleep. Charging is important inorder for the robot 100 to move. The robot 100 in this embodiment alsoacts when a priority event occurs, even when being charged, or even whenthe remaining battery charge is slight. According to this kind ofcontrol, the robot 100 can have flexibility in behavior that is not tooregulated by the remaining battery charge.

When interacting with an owner, the robot 100 frequently executesvarious motions, because of which power consumption also increases. Whenthe power consumption pace is faster than in the consumption plan, it isdifficult for the robot 100 to select a high-load motion. Because ofthis, the robot 100 is energetic when with a person, but the robot 100swiftly becomes quiet when the person subsequently departs. Being happywhen playing with a person, but becoming tired when playing too much,can be expressed by behavior.

The activity monitoring unit 242 recording the operation history of therobot 100 is also effective when seeing a lifestyle pattern of the robot100. For example, when seeing information such as being quiet in theevening and moving energetically on Saturdays, there is an advantage inthat a person's lifestyle pattern can be reconfirmed via the robot 100.

The invention not being limited to the heretofore described embodimentor a modified example, components can be changed or embodied withoutdeparting from the scope of the invention. Various inventions may beformed by a multiple of the components disclosed in the heretoforedescribed embodiment or the modified example being combined asappropriate. Also, some components may be eliminated from the total ofcomponents shown in the heretofore described embodiment or the modifiedexample.

Although a description has been given assuming that the robot system 300is configured of one robot 100, one server 200, and the multiple ofexternal sensors 114, one portion of the functions of the robot 100 maybe realized by the server 200, and one portion or all of the functionsof the server 200 may be allocated to the robot 100. One server 200 maycontrol a multiple of the robot 100, or a multiple of the server 200 maycontrol one or more of the robot 100 in cooperation.

A third device other than the robot 100 and the server 200 may manageone portion of functions. A collection of the functions of the robot 100and the functions of the server 200 described in FIG. 7 can also becomprehensively grasped as one “robot”. It is sufficient that a methodof distributing the multiple of functions needed in order to realize theinvention with respect to one or multiple items of hardware isdetermined with consideration to the processing capability of each itemof hardware, specifications required of the robot system 300, and thelike.

As heretofore described, “the robot in a narrow sense” is the robot 100excluding the server 200, but “the robot in a wide sense” is the robotsystem 300. It is thought that there is a possibility of many functionsof the server 200 being integrated in the robot 100 in future.

In this embodiment, a motion of the robot 100 is selected based on theload table 170. In addition to this, a configuration may be such that aspecific motion is selected only when the remaining battery charge iswithin a predetermined range, or conversely, a configuration may be suchthat a specific motion is not a target of selection.

As a method of changing a motion selection algorithm, the processingload of the motion may be caused to change by replacing or eliminatingone portion of the unit motions configuring the motion. In thisembodiment, the motion processing load is fixed, and motion selectioncorresponding to the remaining battery charge or the like is carried outby causing the motion selection probability to change. The motionprocessing load may be changed with the motion selection probabilityremaining fixed. For example, it is sufficient that the motionprocessing load is caused to change by a unit motion being added oreliminated. A motion interval may be adjusted, or actuator speed may beadjusted. There is a case in which the processing load can be reducedwhen actuator speed is reduced.

According to this kind of control method, behavioral characteristicssuch that a low-charge motion is more likely to be executed, and ahigh-load motion is less likely to be executed, the smaller theremaining battery charge becomes can be realized.

The robot 100 becomes quiet when the remaining battery charge becomessmaller than in the consumption plan, but conversely, the activityamount of the robot 100 may be temporarily raised even when theremaining battery charge becomes small. In this way, unexpectedness ofbehavior of the robot 100 may be secured without being excessivelyregulated by the remaining battery charge.

In addition to the activity amount and the time band, the consumptionplan may be changed based on the time of year, whether the day is aholiday or a weekday, the air temperature, the weather, and the like.

When nobody is present, the robot 100 may be charged even when theremaining battery charge has not reached the lower limit value E1. Byactively charging when nobody is watching, adjustment may be carried outso that a time of activity and a time when the robot 100 is withsomebody coincide.

The basic activity graph line 190 may be set for each robot 100. Aconfiguration may be such that the high activity graph line 192 islikely to be selected for the robot 100 that is in a lively home, andthe robot 100 is likely to be set to the low activity graph line 194 ina quiet home. The behavioral characteristics of the robot 100 can beprovided with individuality by the basic activity graph line 190 beingcaused to change for each robot 100.

By utilizing the operation history, a future activity amount of therobot 100 can be predicted. For example, even when the remaining batterycharge becomes smaller than in the consumption plan, there is apossibility that the consumption plan can be adhered to withoutrestricting the activity amount when in a time band in which an event isunlikely to occur. In this way, the operation control unit 222 mayselect a motion based on the remaining battery charge and a predictedfuture value of the consumption plan.

When called by an owner, the robot 100 heads toward the owner when theremaining battery charge is equal to or greater than a threshold E3. Aconfiguration may be such that when the remaining battery charge is lessthan the threshold E3 but equal to or greater than a threshold E4 (<E3),the robot 100 does not respond to a first call, but responds to a secondcall. A configuration may be such that when the remaining battery chargeis less than the threshold E4 but equal to or greater than a thresholdE5 (<E4), the robot 100 only responds when called in a loud voice. Inthis way, behavioral characteristics such that behavior becomes moresluggish when the remaining battery charge decreases are alsoconceivable. The thresholds E3, E4, and E5 may be set in accordance withthe familiarity of an owner.

In the same way, the smaller the remaining battery charge becomes, thefurther the actuator operating amount may be lowered, or the furthersensitivity with respect to an action map may decrease.

In this embodiment, a description has been given with the robot 100 thatmoves on the front wheel 102 and the rear wheel 103 as a subject, butthe invention is also applicable to a walking robot, such as a robotthat walks on two legs or a robot that walks on four legs. Inparticular, the value of applying the invention is particularly high fora robot that has a large number of actuators and moves in many ways.

Operating Mode

FIG. 13 is a functional block diagram of the robot system 300 in a firstmodified example.

In the robot system 300 of the first modified example, the dataprocessing unit 136 includes an eye generating unit 250, an eye displayunit 252, and a mode selection unit 254 in addition to the operationcontrol unit 150, the recognizing unit 156, and the remaining batterycharge monitoring unit 172. The eye generating unit 250 generates an eyeimage (to be described hereafter). The eye display unit 252 causes aneye image to be displayed in the eye 110. The mode selection unit 254selects an “operating mode” of the robot 100. Operating modes will bedescribed hereafter. Also, the drive mechanism 120 includes variouskinds of actuator 256. Herein, the actuator 256 is a collective term forthe various kinds of actuator described in connection with FIG. 2 andthe like. The operation control unit 150 transmits an actuating signalto the actuator 256, thereby driving the actuator 256. Rotation of theactuator 256, or a direction, speed, and amount of movement, arespecified by the actuating signal.

FIG. 14 is an external view of the eye image 174.

The eye 110 of the robot 100 is formed as a display on which the eyeimage 174 is displayed. The eye generating unit 250 generates the eyeimage 174 to include a pupil image 164 and a periphery image 168. Theeye generating unit 250 also displays the eye image 174 as a movingimage. Specifically, the eye generating unit 250 represents a line ofsight of the robot 100 by moving the pupil image 164. Also, a blinkingoperation is executed at a predetermined timing. The eye generating unit250 represents a large variety of movements of the eye image 174 inaccordance with various operation patterns. The eye display unit 252causes the generated eye image 174 to be displayed on a monitor of theeye 110. The monitor desirably has a curved form, in the same way as ahuman eyeball.

The pupil image 164 includes a pupillary region 258 and a corneal region162. Also, a catch light 166 for expressing a reflection of externallight is also displayed in the pupil image 164. Rather than shiningowing to a reflection of external light, the catch light 166 of the eyeimage 174 is an image region expressed as a high-luminance region by theeye generating unit 250.

The eye generating unit 250 can move the pupil image 164 vertically andhorizontally on the monitor. When the recognizing unit 156 of the robot100 recognizes a moving object, the eye generating unit 250 generates anoperation pattern (moving image data) such that orients the pupil image164 in a direction in which the moving object exists. The eye displayunit 252 expresses a “gaze” of the robot 100 by causing the display ofthe eye image 174 to change in accordance with the operation pattern.

The eye generating unit 250 not only moves the pupil image 164 relativeto the periphery image 168, but can also represent a half-closed eye ora closed eye by causing an eyelid image to be displayed. The eyegenerating unit 250 may represent an aspect of the robot 100 sleeping bydisplaying a closed eye using the eyelid image, or may represent therobot 100 being in a half-asleep state, that is, a state of nodding offto sleep, by covering three-quarters of the load table 170 with theeyelid image, then shaking the eyelid image.

FIG. 15 is an operating mode transition diagram.

Operating modes are broadly divided into a “normal mode M1” and a “powersaving mode M2”. The power saving mode M2 further includes an “observingmode M21 (a first mode)” and a “sleeping mode M22 (a second mode)”. Thepower saving mode M2 is an operating mode such that power consumption isrestricted more than in the normal mode M1. Because of this, theactivity amount of the robot 100 is restricted more when in the powersaving mode M2 than when in the normal mode M1, and the robot 100 isquieter. The operation control unit 150 may limit a supply of power tothe actuator 256 more in the power saving mode M2 than when in thenormal mode M1. The operation control unit 150 may limit the kinds ornumber of actuators 256 that form control targets in the power savingmode M2, or may set the interval (heretofore described) connecting unitmotions to be longer than when in the normal mode M1. The operationcontrol unit 150 may refer to the load table 170, and eliminate a motionwith a processing load (load value) of a predetermined value or greater,or in other words, a motion with a large power consumption, as aselection target. The operation control unit 150 may provide a limit tothe speed of movement of the robot 100 in the power saving mode M2.

Hereafter, a description will be given assuming that the robot 100 canmove in the normal mode M1, but that the robot 100 cannot move in thepower saving mode M2.

The eye generating unit 250 can cause the eye image 174 to change in theobserving mode M21 of the power saving mode M2. Also, the operationcontrol unit 150 can drive the head portion frame 316 (neck) in theobserving mode M21. However, the operation control unit 150 cannot causethe robot 100 to travel by driving the front wheel 102. Although therobot 100 does not move in the observing mode M21, the robot 100 adoptsa behavioral aspect of gazing at a moving object such as a person,another robot 100, or a pet, or in other words, a behavioral aspect ofnot moving, but monitoring and observing a periphery. The observing modeM21 corresponds to “a state of being awake but resting”.

The eye generating unit 250 closes the eyelid, causing the eye image 174that appears to be sleeping to be displayed, in the sleeping mode M22 ofthe power saving mode M2. The operation control unit 150 stops theoperation of all the actuators 256. As heretofore described, the supplyof power to the processor 122 may be stopped in the sleeping mode M22,but the supply of power to the monitor of the eye 110 is maintained. Thesleeping mode M22 corresponds to a “sleeping state”.

As the operation of the robot 100 is stopped in the power saving mode M2of the first modified example, power consumption is restricted incomparison with the normal mode M1. As the operation of all theactuators 256 is stopped in the sleeping mode M22, power consumption isrestricted even further than in the observing mode M21. In the firstmodified example, the operation control unit 150 causes the processor122 to be suspended in the sleeping mode M22. Specifically, not only isa clock of the processor 122 stopped, but the supply of power to theprocessor 122 also stops. An execution state of the processor 122 issaved in the memory, and the supply of power to the memory (storagedevice 124) is maintained. “Suspending” in this case is the same as asuspension method executed in a general personal computer. Suspensionand return from suspension may be realized using a control circuitindependent of the processor 122.

This kind of control method is such that when the robot 100 shifts froman active state (the normal mode M1) to a quiet state (the observingmode M21), and furthermore, reaches a state of appearing to be sleeping(the sleeping mode M22), a hardware (electronic circuit) activity levelcan also be lowered in conjunction. In other words, when the hardwareactivity level is lowered, an expression of behavior such that aconsciousness level of the robot 100 appears to be dropping can berealized. In another modified example, a motion that expresses a stateof nodding off to sleep may be carried out between leaving the observingmode M21 and reaching the sleeping mode M22.

When a “first transition condition” is satisfied in the normal mode M1,the mode selection unit 254 changes the operating mode from the normalmode M1 to the observing mode M21 (S1). It is sufficient that the firsttransition condition is defined arbitrarily. For example, the firsttransition condition may be seen to be satisfied when the amount ofpower consumed per unit time reaches a predetermined threshold orgreater, when the remaining charge of the battery 118 (rechargeablebattery) reaches a predetermined threshold or less, or when a state inwhich the recognizing unit 156 does not detect a moving object (aperson, a pet, or another robot 100) in a periphery, using a sensinginstrument such as the camera, continues for a first time T1 or longer.

When a “second transition condition” is satisfied in the observing modeM21, the mode selection unit 254 changes the operating mode from theobserving mode M21 to the sleeping mode M22 (S2). It is sufficient thatthe second transition condition is also defined arbitrarily. Forexample, the second transition condition may be seen to be satisfiedwhen the remaining charge of the battery 118 (rechargeable battery)reaches a predetermined threshold or less, when a predetermined time orlonger elapses after shifting the state to the observing mode M21, orwhen a state in which the recognizing unit 156 does not detect a movingobject continues for a second time T2 (>T1) or longer.

When a “return event” occurs in the power saving mode M2, the modeselection unit 254 changes the operating mode from the power saving modeM2 to the normal mode M1 (S3). Two kinds of return event, those being a“first return event” and a “second return event”, are defined. When afirst return event occurs, the mode selection unit 254 causes theoperating mode to return from the power saving mode M2 to the normalmode M1 in the case of both the observing mode M21 and the sleeping modeM22. When a second return event occurs when in the observing mode M21,the mode selection unit 254 causes the operating mode to return from thepower saving mode M2 (observing mode M21) to the normal mode M1.However, when a second return event occurs when in the sleeping modeM22, the mode selection unit 254 does not change the operating mode.

A first return event is defined as a phenomenon that causes the“sleeping (corresponding to the sleeping mode M22)” robot 100 to “awake(corresponding to the normal mode M1)”. Specifically, a first returnevent may be seen to have occurred when there is detection of speech ofa first volume V1 or greater, or detection of a touch on the robot 100.

A second return event is defined as a phenomenon that causes the“observing (corresponding to the observing mode M21)” robot 100 toreturn to a normal state (corresponding to the normal mode M1), but isnot sufficient to cause the “sleeping (corresponding to the sleepingmode M22)” robot 100 to awake. That is, a second return event isdesirably defined as a phenomenon whose effect on the “senses” of therobot 100 is small in comparison with that of a first return event.Specifically, a second return event may be seen to have occurred whenthere is detection of speech that is of a second volume V2 V1) orgreater and less than the first volume V1, or detection of a movingobject by the recognizing unit 156. Also, in addition to a sense ofsight, a sense of hearing, and a sense of touch, detection of a smell ora temperature change may be defined as a return event. In all cases, itis sufficient that a return event is a phenomenon that occurs in theexternal environment of the robot 100, and that can be detected by asensor corresponding to the sense of sight, the sense of hearing, thesense of touch, or a sense of smell of the robot 100.

A dedicated motion (hereafter called a “start-up motion”) is correlatedto each of multiple kinds of return event. When a first return event X1occurs in the sleeping mode M22, the operation control unit 150 executesa start-up motion Y1 correlated to the first return event X1. Forexample, when a first return event of “being spoken to from behind”occurs, the operation control unit 150 may perform a behavioralexpression of “being surprised at being spoken to suddenly” by executinga start-up motion causing the front wheel 102 of the robot 100 to movevertically. In the same way, various kinds of start-up motion aredefined for a second return event.

In addition to this, standing from a sitting state by putting out thefront wheel 102, causing the body 104 to shake, changing an orientationto a direction in which a return event has occurred by causing the headportion frame 316 or the body 104 to rotate, causing the eye image 174to blink, causing the arm 106 to wave, and the like, are conceivable asstart-up motions.

It is not necessary that a return event and a start-up motion arefixedly correlated as a pair. As shown in the motion selection table 180of FIG. 8 , a multiple of start-up motions are correlated to one returnevent, and the operation control unit 150 may select a start-up motionin accordance with a selection probability. A large variety ofbehavioral expressions such as, for example, approaching because ofbeing spoken to when observing a periphery, being surprised and runningaway because of being awoken by a loud voice when sleeping, orpretending not to notice despite being spoken to when in the observingmode M2, can be performed by diversifying return events and start-upmotions.

Operation Restriction

When the remaining charge of the battery 118 reaches a reference valueor lower, the operation control unit 150 restricts the operation of theactuator 256 of each portion (hereafter called “operation restriction”).Specifically, operation restriction may be a setting of a limit valuefor an operating range (for example, a possible angle of rotation) andan operating speed of the actuator 256. Operation restriction may be alimiting of the number or kinds of the actuator 256 that can operateamong the multiple of actuators 256, or may be a lengthening of theinterval connecting unit motions compared with a normal time. Theoperating amount of the actuator 256, or in other words the output ofthe actuator 256, may be restricted, or the power supplied to theactuator 256, or in other words the input of the actuator 256, may berestricted. Operation restriction may also be a changing of theoperating mode from the normal mode M1 to the power saving mode M2(observing mode M21).

When the remaining battery charge reaches a predetermined value, lessthan 30% for example, the operation control unit 150 may lower the totalamount of power supplied to the actuator 256 per certain time. When theremaining battery charge becomes less than 30%, the operation controlunit 150 may restrict power consumption by changing the consumption plandata from the one-hour plan 182 to the three-hour plan 184, therebyexpressing a quieting down of the movement of the robot 100. Theoperation control unit 150 may provide an operating limit for eachactuator. For example, drag accompanying a transformation of the outerskin 314 is generated when bending the neck, because of which the dragincreases as an angle at which the neck is bent increases, and a largepower consumption is needed. Empirically, drag increases sharply with acertain angle as a boundary. Taking this boundary as an operation anglethreshold, power consumption may be restricted by controlling so thatthe neck is not bent to the threshold or beyond when restrictingoperation.

When the amount of consumption per unit time of the remaining batterycharge is equal to or greater than a predetermined threshold, theoperation control unit 150 may restrict the operation of the actuator256. According to this kind of control method, behavior of being tiredand becoming quiet as a reaction to moving energetically for a shorttime can be expressed. In addition to this, the operation of one or moreactuators 256 may be restricted for the same reason when the operatingtimes per unit time of all actuators 256 exceed a predeterminedthreshold, when a distance moved per unit time by the robot 100 exceedsa predetermined threshold, or when an energization time of the actuator256 exceeds a predetermined time.

The further the remaining battery charge decreases, the more stronglythe operation control unit 150 may restrict the operation of theactuator 256. For example, the operation control unit 150 may restrictthe angle through which a certain one of the actuators 256 can rotatefrom 180 degrees to 150 degrees when the charge ratio (remaining batterycharge) becomes less than 50%, and restrict the angle to 100 degreeswhen the charge ratio becomes less than 30%. By applying this kind ofrestriction, behavior wherein “sharpness” of movement of the robot 100diminishes further the further the remaining battery charge decreasescan be expressed.

When restricting operation, the operation control unit 150 may restrictoperation with priority from an actuator with large power consumption.An actuator 379 that moves the front wheel 102 has a larger powerconsumption than an actuator 326 that moves the neck. Meanwhile, anactuator (not shown) that moves the arm 106 has a smaller powerconsumption than the actuator 326. When the remaining battery chargedecreases, the operation control unit 150, firstly, may restrict theoperation of, or stop, the actuator 379, and subsequently restrict theoperation of, or stop, the actuator 326, thereby realizing a phasedoperation restriction.

When the remaining battery charge becomes smaller than a predeterminedvalue, the operation control unit 150 lowers the total amount of power(an upper limit value) supplied to each actuator 256. By distributingdesignated power to each actuator 256, the operation control unit 150controls each actuator 256 in a state in which the total amount isregulated.

The robot 100 expresses by behavior an emotion or consciousness of therobot 100 by controlling the multiple of actuators 256. A certain kindof emotion can be expressed by changing a magnitude or a speed of agesture. For example, when “pleasure” is expressed by behavior on adaily basis by “turning round and round”, “shaking the head to the leftand right”, and “waving the arm”, it might be that “turning round andround” and “shaking the head to the left and right” can convey pleasureeven without “waving the arm”. That is, an emotion can be expressed evenwhen one portion of movements configuring a movement differs fromnormal, or is missing.

“Pleasure” is expressed by an operation of “turning round and round”, anoperation of “waving the arm”, and an operation of “shaking the neckportion to the left and right” being executed simultaneously. When theremaining battery charge decreases, the supply of power to the actuatorthat drives the arm is stopped, eliminating the operation of “waving thearm”, and “pleasure” can be expressed even using only the operation of“turning round and round” and the operation of “shaking the neck portionto the left and right”. When the remaining battery charge decreasesfurther, the supply of power to the actuators that drive the wheels mayalso be stopped, and “pleasure” expressed using only the operation of“shaking the neck portion to the left and right”. When the remainingbattery charge decreases further, pleasure may be expressed using onlythe operation of “waving the arm” or the pupil.

The operation control unit 150 expresses an emotion while distributingpower to each actuator within the range of the total amount (upper limitvalue) of power. A motion and a combination of motions may be correlatedto various kinds of emotion, such as “pleasure”, “dissatisfaction”, and“unease”. When executing a motion correlated to “pleasure”, there areimportant actuators and actuators that are not so important. Forexample, an actuator that moves the neck may be more important than anactuator that moves the arm. When the amount of power consumption perunit time exceeds a threshold, or when the remaining battery charge isequal to or lower than a threshold, the operation control unit 150 maystop the supply of power to an actuator of low importance, the actuatorthat moves the arm for example, when expressing “pleasure”.

Also, rather than correlating an emotion expression and an importantactuator, a level of priority may simply be provided for an actuator.For example, as the neck is an important part in the robot 100expressing an emotion, the operation control unit 150 need not regulatethe power supply to the actuator 326, which moves the neck. In this way,in addition to giving priority to an actuator with low powerconsumption, priority may be given to an actuator of high importance foran emotion expression.

The activity monitoring unit 242 may index the “activity amount” of therobot by measuring an operating state, for example, the energizationtime, power consumption, and the like, of each actuator. When theactivity amount (the total activity amount of all the actuators) perunit period of the robot 100 exceeds a predetermined amount, theoperation control unit 150 may temporarily restrict the activity amountof the robot 100. Specifically, the operation control unit 150 may stopor reduce the supply of power to an actuator with a low level ofpriority, or an actuator with large power consumption.

Charging Operation

FIG. 16 is an external view of a charging station 260.

The charging station 260 is a charger of the robot 100, and has aninternal space that houses the robot 100. Charging is started by therobot 100 entering the charging station 260 (charger) and adopting apredetermined posture.

The charging station 260 includes a table 270, a slope 262 that forms asmooth bridge between an upper surface of the table 270 and the floorsurface F, and a frame 264 provided in a periphery of the table 270. Amark M that is used as a guide when the robot 100 enters the chargingstation 260 is applied to a center of the table 270. The mark M is acircular region of a color differing from that of the table 270.

The frame 264 includes a decorative member 266 that encloses theperiphery of the table 270. The decorative member 266 is obtained by alarge number of decorative pieces with a tree leaf as a motif beingplaced one on another, and creates an image of a hedge. A power supplyconnection terminal 268 is provided in a position somewhat offset fromthe central mark M in the table 270.

The remaining battery charge monitoring unit 172 of the robot 100monitors the remaining charge of the battery 118. When the remainingbattery charge (charge amount) reaches a predetermined threshold orless, when the charge ratio is 30% or less for example, the robot 100heads toward the charging station 260. The robot 100 receives a wirelesssignal from a communicator 272 incorporated in the charging station 260.The robot 100 sets the charging station 260 as a movement target pointin accordance with the wireless signal.

The robot 100 films the mark M when entering the charging station 260,and controls a direction of travel of the robot 100 with the mark M as aguide. After the robot 100 enters the charging station 260, theconnection terminal 268 is connected to a connection terminal providedin a bottom portion of the robot 100. Because of this, charging circuitsof each of the robot 100 and the charging station 260 attain aconductive state.

However, due to various reasons such as an obstacle being placed in anentrance of the charging station 260, the charging station 260 fallingsideways, or a failure of the connection terminal 268, a situationwherein the robot 100 cannot be connected to the charging station 260normally is also envisaged. After setting the charging station 260 as amovement target point, the operation control unit 150 attempts aconnection with the charging station 260. When the attempt fails apredetermined number of times (an arbitrary number of one or more), thefirst transition condition is satisfied. That is, when a predeterminednumber of connection attempts fail, the mode selection unit 254 changesthe operating mode from the normal mode M1 to the power saving mode M2.According to this kind of control method, power wastage due tocontinually failing in attempts to connect to the charging station 260can be prevented.

Meanwhile, when the robot 100 detects a moving object, particularly auser, the robot 100 may continue attempting to connect to the chargingstation 260, without changing to the power saving mode M2. This isbecause the user may help in the attempt to charge the robot 100, suchas by removing an obstacle in front of the charging station 260.

When the recognizing unit 156 detects an obstacle in a path along whichthe robot 100 heads toward the charging station 260, the mode selectionunit 254 may cause the first transition condition to be satisfied, eventhough no failure of a connection attempt has actually occurred. Forexample, the robot 100 cannot connect to the charging station 260 whenthe charging station 260 is installed in the living room, the robot 100exists in a room differing from the living room, and a door between theroom and the living room is closed. In this case, the door forms an“obstacle”. At this time, the mode selection unit 254 may change fromthe normal mode M1 to the power saving mode M2 when nobody is in theperiphery.

As heretofore described, the robot 100 in the first modified exampleautonomously causes the operating mode to change from the normal mode M1to the power saving mode M2 when the first transition condition issatisfied. Because of this, for example, power can be saved effectivelyand diligently by grasping realistic timing, even when restricting powerconsumption when there is no user in the periphery, and the like.Meanwhile, the robot 100 can return automatically from the power savingmode M2 to the normal mode M1 when in a situation in which it is highlynecessary to respond to the external environment, as when spoken to orwhen detecting a user. In particular, the robot 100 can easily bereturned from the power saving mode M2 to the normal mode M1 simply byspeaking to the robot 100.

By executing a start-up motion corresponding to a return event whenreturning from the power saving mode M2 to the normal mode M1,behavioral characteristics such that the robot 100 appears to respondsubconsciously (the start-up motion) because an incident sufficient towake the robot 100 up (the return event) has occurred in a state of alow level of consciousness (the power saving mode M2) can be expressed.When detecting a user in the observing mode M21, the robot 100 canreturn from the observing mode M21 to the normal mode M1 in a naturalway by approaching the user while waving the arm 106 (a start-upmotion).

Not being limited to an operating mode such as the power saving mode M2,power may be saved by reducing the operating amount of the actuator 256(operation restriction) when the remaining charge of the battery 118decreases. Using various kinds of operation restriction, power savingcan be realized while expressing by behavior lethargy or fatigue in themovement of the robot 100.

In the observing mode M21, the robot 100 is quiet in comparison withwhen in the normal mode M1, but expresses behavior of appearing to beaware of a peripheral environment by moving the eye image 174 or thehead portion frame 316. When a moving object is detected beside therobot 100, the eye display unit 252 may gaze at the moving object bymoving the eye image 174. The observing mode M21, so to speak, expressesa state wherein the body is being rested but the consciousness isworking. In the sleeping mode M22, the eye 110 and the actuator 256 donot move, because of which there is a further power saving in comparisonwith the observing mode M21. The sleeping mode M22, so to speak, is anoperating mode that expresses a state wherein the consciousness is notworking (a sleeping state). In response to the state wherein theconsciousness is not working, the activity level of the robot 100 and anactivity level of an actual electrical circuit can be naturallysynchronized by suspending the processor 122. In the sleeping mode M22,not being limited to suspending, hibernation that causes a working statein the memory to be saved on the hard disk may be executed. Also, theprocessor 122 may be caused to return from the suspended state by areturn event being detected by an interrupt circuit differing from theprocessor 122, and an interrupt signal being generated.

When a return event occurs, the operating mode of the robot 100 ischanged from the power saving mode M2 to the normal mode M1. At thistime, the robot 100 executes a start-up motion. Because of this, forexample, a way of being involved that teases the robot 100, bysurprising the robot 100 by speaking in a loud voice to the robot 100 inthe power saving mode M2, can be adopted. Meanwhile, merely passingbeside the robot 100 does not form a first return event, because ofwhich the robot 100 in the sleeping mode M22 does not return to thenormal mode M1. A user may show consideration by behaving quietly so as“not to wake up” the robot 100 in the sleeping mode M22 (the sleepingrobot 100). This kind of involvement, wherein a user shows considerationto the robot 100, or in other words, the robot 100 causes a user to actcarefully, can also be adopted.

The above description states that operation restriction is carried outwhen the remaining battery charge decreases. In addition to a decreasein the remaining battery charge, various conditions are conceivable as atrigger for operation restriction. When the recognizing unit 156 detectsa command via speech from a user, for example, when the recognizing unit156 detects a speech command including predetermined words such as “keepquiet”, the operation control unit 150 may carry out operationrestriction. When the recognizing unit 156 detects that the externaltemperature has deviated from a predetermined range, for example, at “acold time” of a first temperature T1 or less or “a hot time” of a secondtemperature T2 (>T1) or greater, the operation control unit 150 maycarry out operation restriction. Also, when a total operating time ofthe robot 100 exceeds a threshold, that is, when the robot 100 “ages”,the operation control unit 150 may carry out operation restriction.

In the observing mode M21, the eye generating unit 250 may express astate of the robot 100 “being awake”, and looking exactly as thoughobserving the periphery, by causing the eye image 174 to open, andmoving the pupil image 164 to the left and right. That is, in theobserving mode M21, a motion of slowly moving the line of sight andobserving the periphery is executed, without carrying out an advancedimage processing or recognition process that applies a high load to CPUresources. Because of this, power consumption is restricted, and therobot 100 being in the process of operating can be expressed. Meanwhile,in the sleeping mode M22, the eye generating unit 250 may express“sleep” by causing the eye image 174 to close.

The processor 122 of the robot 100 may be an aggregation of a mainprocessor and a sub-processor. The main processor realizes a basicfunction of the data processing unit 136. Meanwhile, the sub-processoris a processor that operates on an operating voltage lower than that ofthe main processor. A computer program that realizes the functions ofthe recognizing unit 156 and the operation control unit 150 is mainlyexecuted in the main processor. Meanwhile, functions with a small totalload of the eye generating unit 250, the eye display unit 252, the modeselection unit 254, the remaining battery charge monitoring unit 172,and the like, are mainly realized by the sub-processor. For example, thefunctions of the eye generating unit 250 and the like may be realized bya low-voltage drive compact computer.

When changing the operating mode from the normal mode M1 to the powersaving mode M2, the sub-processor may cause the main processor to stop.For example, the sub-processor may cause a clock of the main processorto stop. That is to say, it is sufficient that the sub-processorsuspends the main processor. Further, depending on a computingcapability of the sub-processor, the eye generating unit 250 may causethe eye image 174 to operate. When a return event is detected, the modeselection unit 254 may cause the clock of the main processor to restartby applying an interrupt to the main processor. According to this kindof control method, a minimum necessary operation of the eye image 174and the like can be realized by the sub-processor, which has small powerconsumption, in the power saving mode M2. In other words, powerconsumption can be restricted, while expressing that the robot 100 isawake, in the observing mode M21.

What is claimed is:
 1. An autonomously acting robot, comprising: aplurality of actuating elements, wherein each of the plurality ofactuating elements is configured to move a corresponding portion of theautonomously acting robot; a non-transitory computer readable mediumconfigured to store instructions thereon; a processor connected to thenon-transitory computer readable medium, wherein the processor isconfigured to execute the instructions for: monitoring a remainingcharge of a power source of the autonomously acting robot; selecting amotion of a plurality of motions for the autonomously acting robot basedon the remaining charge and a power consumption of the motion, whereinselecting the motion comprises prioritizing movement of each of theplurality of actuating elements associated with the motion based on apower consumption for each of the each of the plurality of actuatingelements associated with the motion; and a drive mechanism configured toexecute the selected motion.
 2. The autonomously acting robot accordingto claim 1, wherein the processor is configured to execute theinstructions for selecting the motion based on a probability for each ofthe plurality of motions, wherein the probability for each of theplurality of motions changes based on the remaining charge.
 3. Theautonomously acting robot according to claim 2, wherein the processor isconfigured to execute the instructions for selecting the motion byreferring to a load table in which motion of the autonomously actingrobot and a processing load of the processor accompanying execution ofthe motion are correlated, and a probability of selecting a motion ofthe plurality of motions having a small processing load increases as theremaining charge decreases.
 4. The autonomously acting robot accordingto claim 1, wherein the processor is configured to execute theinstructions for changing behavioral characteristics of the autonomouslyacting robot in accordance with a difference between a predictedremaining charge, after the selected motion, and the remaining charge.5. The autonomously acting robot according to claim 1, wherein theprocessor is configured to execute the instructions for setting thepower consumption per unit period of the motion based on an operatingtime band of the autonomously acting robot.
 6. The autonomously actingrobot according to claim 1, wherein the processor is configured toexecute the instructions for: recording an operation history of theautonomously acting robot; and setting the power consumption based onthe operation history.
 7. The autonomously acting robot according toclaim 1, wherein the processor is configured to execute the instructionsfor selecting the motion using a selection probability for each of theplurality of motions, wherein the selection probability is inverselyrelated to a processing load of a corresponding motion of the pluralityof motions.
 8. The autonomously acting robot according to claim 1,wherein the processor is configured to execute the instructions foradjusting a selection probability of each of the plurality of motions,in response to detecting a moving object, so that a ratio increases,wherein the ratio is the selection probability of a corresponding motionof the plurality of motions having a high processing load with respectto a selection probability of a corresponding motion of the plurality ofmotions with a low processing load.
 9. The autonomously acting robotaccording to claim 1, wherein the processor is configured to execute theinstructions for: determining an occurrence of an event; and changing aselection probability of each of the plurality of motions based on theoccurrence of the event and the remaining charge.
 10. The autonomouslyacting robot according to claim 9, wherein the processor is configuredto execute the instructions for selecting, in response to occurrence ofa predetermined priority event, a motion of the plurality of motionsassociated to the predetermined priority event, regardless of theremaining charge.
 11. An autonomously acting robot, comprising: anon-transitory computer readable medium configured to store instructionsthereon; a processor connected to the non-transitory computer readablemedium, wherein the processor is configured to execute the instructionsfor: monitoring a remaining charge of a power source for powering theautonomously acting robot; determining whether a predetermined priorityevent has occurred; selecting a motion of a plurality of motions for theautonomously acting robot, wherein the selecting the motion comprisesselecting a predetermined motion of the plurality of motions in responseto a determination that the predetermined priority event has occurred,and an initial operation of the predetermined motion comprises removingthe autonomously acting robot from a charger regardless of the remainingcharge during performing the predetermined motion; a drive mechanismconfigured to execute the selected motion.
 12. The autonomously actingrobot according to claim 11, wherein the predetermined priority eventcorresponds to detection of a person in a monitoring area.
 13. Theautonomously acting robot according to claim 11, wherein thepredetermined priority event corresponds to detection of a person in themonitoring area and a familiarity setting associated with the personexceeding a predetermined threshold.
 14. An autonomously acting robot,comprising: a non-transitory computer readable medium configured tostore instructions thereon; a processor connected to the non-transitorycomputer readable medium, wherein the processor is configured to executethe instructions for: monitoring a remaining charge of a power sourcefor powering the autonomously acting robot; measuring an activity amountof the autonomously acting robot; selecting a motion of a plurality ofmotions for the autonomously acting robot, wherein selecting the motioncomprises temporarily restricting the activity amount of theautonomously acting robot based on the remaining charge and a predictedfuture value of a first power consumption plan of the remaining charge;a drive mechanism configured to execute the selected motion.
 15. Theautonomously acting robot according to claim 14, wherein the processoris configured to execute the instructions for switching from the firstpower consumption plan to a second power consumption plan based on theremaining charge, wherein the second power consumption plan has a longerduration than the first power consumption plan.
 16. An autonomouslyacting robot, comprising: a non-transitory computer readable mediumconfigured to store instructions thereon; a processor connected to thenon-transitory computer readable medium, wherein the processor isconfigured to execute the instructions for: selecting a normal mode or apower saving mode, wherein a number of actuating elements of theautonomously acting robot that are movable during the power saving modeis less than in the normal mode, and the actuating elements of theautonomously acting robot that are movable during the power saving modeare based on an importance of each of the number of actuating elements;selecting, in response to selecting the power saving mode, a first modeor a second mode, wherein the first mode is selected in response tochanging from the normal mode to the power saving mode, and the secondmode is selected in response to satisfying a predetermined conditionwhile the autonomously acting robot is in the first mode; changing apupil image on a display of the autonomously acting robot in response toselecting the first mode or the second mode, wherein in the first modethe pupil image comprises a moving image, and in the second mode thepupil image is an image of a closed eye.
 17. The autonomously actingrobot according to claim 16, wherein the processor is configured toexecute the instructions for selecting a motion of a plurality ofmotions for the autonomously acting robot; and the autonomously actingrobot further comprises: a drive mechanism configured to execute theselected motion.
 18. The autonomously acting robot according to claim16, wherein the processor is configured to execute the instructions for:changing to the normal mode, whether in the first mode or the secondmode, in response to detection of a first return event, and changing tothe normal mode, when in the first mode in response to detection of asecond return event.
 19. The autonomously acting robot according toclaim 18, wherein the processor is configured to execute theinstructions for maintaining the second mode, when in the second mode,in response to detection of the second return event.
 20. Theautonomously acting robot according to claim 16, wherein the processorcomprises: a first processor configured to select the motion, whereinthe first processor is configured to cease operation in response to achange from the normal mode to the power saving mode; and a secondprocessor configured to change the pupil image, wherein the secondprocessor is configured to continue operation in response to a changefrom the normal mode to the power saving mode.